plot_fairness_pca: Plot fairness PCA

In ModelOriented/FairModels: Flexible Tool for Bias Detection, Visualization, and Mitigation

Plot fairness PCA

Description

Plot pca calculated on fairness_object metrics. Similar models and metrics should be close to each other. Plot doesn't work on multiple fairness_pca objects. Unlike in other plots here other fairness_pca objects cannot be added.

Usage

## S3 method for class 'fairness_pca'
plot(x, scale = 0.5, ...)

Arguments

x	fairness_pca object
scale	scaling loadings plot, from 0 to 1
...	other plot parameters

Value

ggplot2 object

Examples

data("german")

y_numeric <- as.numeric(german$Risk) - 1

lm_model <- glm(Risk ~ .,
  data = german,
  family = binomial(link = "logit")
)

rf_model <- ranger::ranger(Risk ~ .,
  data = german,
  probability = TRUE,
  num.trees = 200,
  num.threads = 1
)

explainer_lm <- DALEX::explain(lm_model, data = german[, -1], y = y_numeric)
explainer_rf <- DALEX::explain(rf_model, data = german[, -1], y = y_numeric)

fobject <- fairness_check(explainer_lm, explainer_rf,
  protected = german$Sex,
  privileged = "male"
)

# same explainers with different cutoffs for female
fobject <- fairness_check(explainer_lm, explainer_rf, fobject,
  protected = german$Sex,
  privileged = "male",
  cutoff = list(female = 0.4),
  label = c("lm_2", "rf_2")
)

fpca <- fairness_pca(fobject)

plot(fpca)

ModelOriented/FairModels documentation built on Aug. 30, 2022, 5:48 p.m.